Search results

The new customer churn prediction (CCP) utilizing deep learning is developed in this work. Initially, the data are collected from the WSDM-KKBox’s churn prediction challenge dataset. Here, the time-varying data and the static data are aggregated, and then the statistic features and deep features with the aid of statistical measures and “Visual Geometry Group 16 (VGG16)”, accordingly, and the features are considered as feature 1 and feature 2. Further, both features are forwarded to the weighted feature fusion phase, where the modified exploration of driving training-based optimization (ME-DTBO) is used for attaining the fused features. It is then given to the optimized and ensemble-based dilated deep learning (OEDDL) model, which is “Temporal Context Networks (DTCN), Recurrent Neural Networks (RNN), and Long-Short Term Memory (LSTM)”, where the optimization is performed with the aid of ME-DTBO model. Finally, the predicted outcomes are attained and assimilated over other classical models.

The features are forwarded to the weighted feature fusion phase, where the ME-DTBO is used for attaining the fused features. It is then given to the OEDDL model, which is “DTCN, RNN, and LSTM”, where the optimization is performed with the aid of the ME-DTBO model.

The accuracy of the implemented CCP system was raised by 54.5% of RNN, 56.3% of deep neural network (DNN), 58.1% of LSTM and 60% of RNN + DTCN + LSTM correspondingly when the learning percentage is 55.

The proposed CCP framework using the proposed ME-DTBO and OEDDL is accurate and enhances the prediction performance.

Flexible return policies are offered by the manufacturers to encourage the retailers announcing a lenient returns scheme to their customers.

This study considers the distribution of durable products in a supply chain where the demand is sensitive to sales effort and retail price. Using a game theoretic framework, the paper presents an assessment of the strategic effect of flexible returns policy announced by the manufacturer under retail competition and highlights its implications on profitability.

Comparative analysis of monopolistic and duopolistic competition provides a better understanding about the repercussions and related facts on offering a flexible returns policy in these environments. It is profitable for the manufacturer to offer a flexible returns policy when there is retail competition than under monopolistic condition.

Practitioners view returns policy offered as an insurance given to the buyers and they infer it to be a better mechanism for doing business. Lenient returns policy promotes the sales by increasing the trust on the retailer and boosts up the perception of quality about the product by lowering the perceived risk for customers.

Effective product return strategies such as being lenient in terms of time, money, effort, scope and exchange can result in increased revenues, lower cost and improved profitability to the manufacturer and retailer, at the same time offering an enhanced level of customer service.

Lean Six Sigma 4.0 has brought about a paradigm shift in customization, automation, value creation and digitalization to achieve excellence in human factors, operations and sustainable development. Despite its potential, LSS 4.0 is still in its nascent stage, with researchers striving to identify the key and relevant components of LSS in relation to Industry 4.0. The present study aims to address this knowledge gap through a literature review and subsequently provide a conceptual framework for LSS within the context of digital transformation.

In this study, the authors have conducted a thorough review of reputable articles published between 2011 and 2022, focusing on the integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0). By using appropriate keywords, the authors identified around 85 relevant articles. The main objective of this integrative literature review was to analyze and extract valuable knowledge from the existing literature on LSS and I4.0. Based on the authors’ findings, a conceptual framework was developed.

The review revealed the motivators, building blocks, tools and challenges of LSS 4.0. The conceptual framework delves into the key aspects of LSS 4.0, focusing on the dimensions of people, process and technology, as well as their subdimensions. These subdimensions serve as the building blocks for developing LSS 4.0 capabilities. The proposed framework visually represents the conceptualization and the relationships among its components.

Only a few conceptual approaches to LSS are developed that include the concepts, new roles and elements of I4.0. As a result, this research investigates the gap in current LSS models preceding I4.0 and develops a conceptual framework to provide a novel and comprehensive summary of the new concepts and components driving nascent and current LSS practices in the digital era.

This study offers practical guidance for implementing LSS in the context of I4.0, emphasizing digital transformation. The findings highlight motivators, building blocks, tools, challenges and spread of LSS 4.0 practices, and present a conceptual framework of LSS 4.0. These insights can help organizations enhance their LSS capabilities and achieve excellence in human factors, operations and sustainable development.

This study aims to make a significant contribution to the model-building efforts of researchers focusing on LSS 4.0. By offering practical guidance, the points discussed in this study help enhance the implementation efforts of practitioners and organizations in the context of I4.0, with a specific focus on digital transformation. The guidance provided takes into account the perspectives of people, processes and technology, providing valuable insights for successful integration.

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of publication trends, article distribution by author, journal, affiliations and country, and article clustering based on keywords, authors and countries. In addition, a literature review was carried out to build a conceptual framework of integrated Lean Six Sigma and Industry 4.0 (LSS 4.0) that encompasses operational, sustainability and human factors or ergonomics aspects.

The literature review of integrated Lean Six Sigma and I4.0 publications published in Scopus and WoS databases in the current decade was conducted for the present study. This study categorizes LSS, I4.0 and related research articles based on publication patterns, journals, authors and affiliations, country and continental-wise distribution and clustering the articles based on keywords and authors from the Scopus and WoS databases from 2011 to 2022 using the search strings “Lean”, “Six Sigma”, “Lean Six Sigma” and “Industry 4.0” in the Title, Abstract and Keywords using Biblioshiny, VOS viewer and Microsoft Excel.

In the recent three years, from 2020 to 2022, LSS 4.0 has been substantially increasing and is seen as an emerging and trending area. This research identifies the most influential authors, most relevant affiliations, most prolific countries and most productive journals and clusters based on keywords, authors and countries. Further, a conceptual framework was developed that includes the impact of operational, sustainability and ergonomic or human factors in LSS 4.0.

This article assists in comprehending the trends and patterns of LSS 4.0. Further, the conceptual framework helps professionals and researchers understand the significance and impact of integrating LSS and Industry 4.0 in the aspects of human factors/ergonomic, sustainability and operations. Also, the research induce professionals to incorporate all these factors while designing and implementing LSS 4.0 in their organization.

This conceptual framework and bibliometric analysis would aid in identifying potential areas of research and providing future directions in the domain of LSS 4.0. It will be beneficial for academicians, professionals and researchers who are planning to apply and integrate techniques of LSS and technologies of I4.0 in their organizations and research.

In this meta-analysis, the authors investigate the relationship between self-construal and conflict management strategies and shed light on the inconsistent findings in the literature. Moreover, they examine the mediating role of face concerns in this relationship. Importantly, the present meta-analysis is the first to test the assumptions of face-negotiation theory with the meta-analytic structural equation modeling (MASEM), which enabled the authors to test the hypothesized relationships in one single model.

The authors used the method of MASEM to test the relationship between self-construal and conflict management and assess the mediating role of face concerns. In this regard, the authors employed one-stage meta-analytic structural equation modeling to perform MASEM and its moderators.

Two hundred fifty-four effect sizes based on thirty-three studies were pooled in this meta-analysis. The authors found that individuals with stronger independent self-construal and stronger self-face concerns were more likely to use forcing. Moreover, the relationship between independent self-construal and forcing was mediated by self-face concerns. Individuals with a stronger interdependent self-construal and individuals with stronger other-face concerns were more likely to use problem-solving and yielding. The relationship between interdependent self-construal and problem-solving and yielding was mediated by other-face concerns. Finally, interdependent self-construal also had an indirect effect, via other-face concern, on avoiding and compromising.

The present meta-analysis is the first effort that the authors are aware of to test the assumptions of face-negotiation theory (FNT) using MASEM method. The authors used one-stage meta-analytic structural equation modeling viewed as the state of the methods to perform MASEM and its moderators. They employed full information meta-analytic structural equation modeling to show the generalizability and heterogeneity of structural equation modeling parameters. They applied studentized deleted residuals to assess outlier analysis and also conducted different methods to perform MASEM to check the robustness of the findings resulted. Finally, the current study adds multiple methods of assessing for publication bias.

The purpose of this work is to gain insights about Lean Six Sigma (LSS) in the Indian context by reviewing the related literature for one decade based on various perspectives, such as author profile, year of publication, type of firm, type of methodology used, type of industry for which the research work is carried out and the key findings from the research.

This study reviews the research related to LSS from the articles published in the reputed journals. The literature used for reviewing is derived from the sources, including Science direct, Google scholar, IEEE, Taylor and Francis Group, Emerald Insight, Springer, Inderscience and Elsevier during the period between 2010 and 2021. Totally, the authors have included 141 LSS-related research articles that are published in the Indian context. The keywords used are Lean Six Sigma, Lean Six Sigma in the Indian context, Lean Sigma and LSS to identify and consolidate the research papers published during this timeframe.

The research papers collected from various reputed journals, including Scopus and non- Scopus enlisted, are classified and grouped under various categories to identify the class of author who publishes more in this field, research trend over the years, the type of firm which implements LSS, the research methodology which is commonly used in LSS and related research and also the key takeaway from these articles are highlighted. Further, the authors have also identified the major contributions of researchers in various sectors during this period in India.

This classification framework and the systematic review help in identifying the research gap and in giving directions for future researchers. It will be useful for researchers and practitioners working on the area of LSS, rural and urban entrepreneurs, start-up managers, professionals working in micro, small and medium enterprises (MSMEs) and executives of the Make in India Project to make India as Aatmanirbhar Bharat Abhiyan. Further, the clear direction of progress over the current decade in manufacturing industries, service sectors and processing industries can help the professionals working in these sectors.

This research aims to conduct a literature review of Lean Six Sigma (LSS) in the Indian context and related research publications and apply bibliometric analysis and the author's visualization to map research trends in this area.

This article conducts a bibliometric analysis of LSS-related research in the Indian context using data gathered from Scopus and Web of Science databases from 2011 to 2022. The review provides information on LSS-related research in the Indian context and evaluates performance based on primary sources, authors, keywords, countries, affiliations, and documents. The analysis employs the Biblioshiny app and Bibliometrix R-tool for data analysis and scientific mapping.

The results of the bibliometric analysis indicate that the LSS culture has widely spread in India. The International Journal of Lean Six Sigma and Production Planning and Control were found to be the most productive sources for publishing LSS-related research articles. Antony J. was identified as the most active author in this field, contributing the most over the years. Among all organizations, NITs have conducted the most comprehensive research on LSS, indicating their significant investment of resources and efforts in studying this methodology and its applications in India. Additionally, the study examined the intellectual, social, and conceptual structures to identify implicit gaps and future research opportunities.

The findings of this study can inform academicians, researchers, practitioners, and policymakers about the state-of-the-art and the specifics of the most prolific studies. This study will facilitate their exploration of emerging research areas in LSS.

To the best of the authors knowledge, this is the first bibliometric analysis of LSS in the Indian context, providing an overview of relevant publications published between 2011 and 2022. This study analyzed 194 articles on LSS in India, which can help researchers and academics identify emerging research areas, suitable collaborators, and relevant journals for future publications.

The paper provides a comprehensive overview of the biases in inventory decisions, under the umbrella of behavioural operations, considering research findings that used experimental methods. Research in this field has gained traction but, to the best of our knowledge, review articles that summarize these research findings are scarce. Hence, there is a need to synthesize the anomalies and biases reported in inventory decision-making literature to gain a more integrated understanding.

This study reviews themes relevant to inventory and behavioural operations management from the articles published in recognized top-tier journals during the period between 2000 and 2020 with an aim to build a classification framework. Further, using a systematic review procedure, the relevant research studies are divided into sub-sections and appropriate search strategies are adopted to pleat more information on inventory ordering biases.

This study presents a classification framework by highlighting the factors influencing the biases in inventory decisions and describes the effects of utility preferences on the decision-making behaviour. It highlights the inventory ordering pattern under unconventional settings and also for different supply chain settings. This systematic review helps in identifying the research gap and in giving directions for future researchers.

The study presents a systematic review and detailed analysis of the research in inventory decision making through a behavioural lens. The study shows a clear direction of progress over the years, and implies new directions for looking beyond placing orders and for moving towards a more integrated approach while making supply chain decisions. It will be useful for researchers and practitioners working on newsvendor decisions, supply chain contracts, behavioural economics, behavioural operations management, bounded rationality theory and experimental economics.

To deal with an increasingly competitive environment, organizations are combining continuous improvement (CI) practices with digitalization to accrue their benefits on operational performance and achieve operational excellence. The purpose of this study was to identify the enablers and inhibitors of digitalization as part of CI projects.

A mixed-methods sequential explanatory research design consisting of an online survey and semi-structured interviews was used to examine how digitalization technologies have been incorporated by organizations in their CI projects.

Key enablers of digitalization were found to be leadership capabilities, strategic direction, stakeholder involvement, system compatibility, data quality and giving employees room to experiment. Knowledge of digitalization was found to affect all these enablers.

The empirical findings are based on a nonprobability sample of Dutch CI practitioners, limiting their generalizability.

The empirical findings highlight the need for organizations to adopt a structured approach to implementing digitalization as part of their CI projects, starting by ensuring that the necessary knowledge and skills are either present or accessible to the organization.

The empirical findings show that enablers of digitalization in the context of CI are strongly interlinked, and thus require a holistic approach.

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.